Performance of the QRISK cardiovascular risk prediction algorithm in an independent UK sample of patients from general practice: a validation study

Assessing mortality risk in Type 2 Diabetes patients with prolonged ASCVD risk factors: the inclusive Poh-Ai predictive scoring system with CAC Score integration

PURPOSE

To enhance the predictive risk model for all-cause mortality in individuals with Type 2 Diabetes (T2DM) and prolonged Atherosclerotic Cardiovascular Disease (ASCVD) risk factors. Despite the utility of the Coronary Artery Calcium (CAC) score in assessing cardiovascular risk, its capacity to predict all-cause mortality remains limited.

METHODS

A retrospective cohort study included 1929 asymptomatic T2DM patients with ASCVD risk factors, aged 40-80. Variables encompassed demographic attributes, clinical parameters, CAC scores, comorbidities, and medication usage. Factors predicting all-cause mortality were selected to create a predictive scoring system. By using stepwise selection in a multivariate Cox proportional hazards model, we divided the patients into three risk groups.

RESULTS

In our analysis of all-cause mortality in T2DM patients with extended ASCVD risk factors over 5 years, we identified significant risk factors, their adjusted hazard ratios (aHR), and scores: e.g., CAC score > 1000 (aHR: 1.57, score: 2), CAC score 401-1000 (aHR: 2.05, score: 2), and more. These factors strongly predict all-cause mortality, with varying risk groups (e.g., very low-risk: 2.0%, very high-risk: 24.0%). Significant differences in 5-year overall survival rates were observed among these groups (log-rank test < 0.001).

CONCLUSION

The Poh-Ai Predictive Scoring System excels in forecasting mortality and cardiovascular events in individuals with Type 2 Diabetes Mellitus and extended ASCVD risk factors.

Ten-Year Cardiovascular Risk as Predicted by the QRISK®3 Calculator in Diabetic Patients Attending a Tertiary Care Teaching Hospital in Central India and Its Application to Stratify Statin Over-Users and Under-Users

BACKGROUND

Cardiovascular disease (CVD) is an important cause of morbidity and mortality in diabetic patients. As such, risk stratification is essential to identify the risk factors of CVD and provide early intervention. The QRISK®3 tool, recommended by the National Institute for Health and Care Excellence (NICE) guidelines, has the option to choose the patient's ethnicity, which is not available in other tools. However, there is a paucity of data regarding the use of this tool in the Indian population. Therefore, this study was planned to predict 10-year CVD risk using the QRISK®3 tool and to determine statin eligibility in diabetic patients.

METHODS

We enrolled diabetic patients visiting our general medicine outpatient department and diabetic clinic in the study. We collected data from clinical and prescription records, as well as through patient interviews. We analyzed the data to determine the 10-year CVD risk using the QRISK®3 risk tool, which is available online. A cut-off QRISK score of 10%, as recommended by the NICE guidelines (2014), was used to stratify patients as "over-users" and "under-users." We also analyzed the data to determine any correlation between other risk factors and QRISK scores.

RESULTS

Of the 134 diabetic patients recruited in this study, 43 (32.09%) had a CVD risk score of <10%, of which 16 (37.21%) were categorized as "over-users." Of the patients, 91 had a CVD risk score of ≥10%, of which 17 (18.68%) were categorized as "under-users." Risk factors showing a positive correlation with QRISK score included duration of diabetes, age, blood pressure treatment, waist circumference, and non-high-density lipoprotein cholesterol level.

CONCLUSION

QRISK score can be useful to predict 10-year CVD risk in the Indian population and to stratify patients as statin over-users and under-users. This tool can be used in the Indian set-up to identify potential candidates for statin initiation.

Exercise Capacity in Very Low Birth Weight Adults: A Systematic Review and Meta-Analysis

There is an association between very low birth weight (VLBW) and cardiovascular morbidity and mortality in adulthood. Aerobic fitness, measured as the maximal oxygen consumption (VO2 max), is a good indicator of cardiopulmonary health and predictor of cardiovascular mortality. Our aim was to determine the effect of birth weight on aerobic exercise capacity and physical activity. We systematically identified studies reporting exercise capacity (VO2 max and VO2 peak) and physical activity levels in participants born at VLBW aged eighteen years or older compared to term-born controls from six databases (MEDLINE, OVID, EMBASE, CI NAHL, CENTRAL, and Google Scholar). Meta-analysis of eligible studies was conducted using a random effect model. We screened 6202 articles and identified 15 relevant studies, 10 of which were eligible for meta-analysis. VLBW participants had a lower VO2 max compared to their term counterparts (-3.35, 95% CI: -5.23 to -1.47, p = 0.0005), as did VLBW adults who had developed bronchopulmonary dysplasia (-6.08, 95% CI -11.26 to -0.90, p = 0.02). Five of nine studies reported significantly reduced self-reported physical activity levels. Our systematic review and meta-analysis demonstrated reduced maximal aerobic exercise capacity in adults born at VLBW compared to term-born controls.

Evidence supporting the choice of a new cardiovascular risk equation for Australia

This article reviews the risk equations recommended for use in international cardiovascular disease (CVD) primary prevention guidelines and assesses their suitability for use in Australia against a set of a priori defined selection criteria. The review and assessment were commissioned by the National Heart Foundation of Australia on behalf of the Australian Chronic Disease Prevention Alliance to inform recommendations on CVD risk estimation as part of the 2023 update of the Australian CVD risk assessment and management guidelines. Selected international risk equations were assessed against eight selection criteria: development using contemporary data; inclusion of established cardiovascular risk factors; inclusion of ethnicity and deprivation measures; prediction of a broad selection of fatal and non-fatal CVD outcomes; population representativeness; model performance; external validation in an Australian dataset; and the ability to be recalibrated or modified. Of the ten risk prediction equations reviewed, the New Zealand PREDICT equation met seven of the eight selection criteria, and met additional usability criteria aimed at assessing the ability to apply the risk equation in practice in Australia.

Cardiovascular disease (CVD) outcomes and associated risk factors in a medicare population without prior CVD history: an analysis using statistical and machine learning algorithms

There is limited information on predicting incident cardiovascular outcomes among high- to very high-risk populations such as the elderly (≥ 65 years) in the absence of prior cardiovascular disease and the presence of non-cardiovascular multi-morbidity. We hypothesized that statistical/machine learning modeling can improve risk prediction, thus helping inform care management strategies. We defined a population from the Medicare health plan, a US government-funded program mostly for the elderly and varied levels of non-cardiovascular multi-morbidity. Participants were screened for cardiovascular disease (CVD), coronary or peripheral artery disease (CAD or PAD), heart failure (HF), atrial fibrillation (AF), ischemic stroke (IS), transient ischemic attack (TIA), and myocardial infarction (MI) for a 3-yr period in the comorbid history. They were followed up for up to 45.2 months. Analyses included descriptive approaches in terms of incidence rates and density ratios, and inferential in terms of main effect statistical/complex machine learning modeling. The contemporary risk factors of interest spanned across the domains of comorbidity, lifestyle, and healthcare utilization history. The cohort consisted of 154,551 individuals (mean age 68.8 years; 62.2% female). The overall crude incidence rate of CVD events was 9.9 new cases per 100 person-years. The highest rates among its component outcomes were obtained for CAD or PAD (3.6 for each), followed by HF (2.2) and AF (1.8), then IS (1.3), and finally TIA (1.0) and MI (0.9).Model performance was modest in terms of discriminatory power (C index: 0.67, 95%CI 0.667-0.674 for training; and 0.668, 95%CI 0.663-0.673 for validation data), equal agreement between predicted and observed events for calibration purposes, and good clinical utility in terms of a net benefit of 15 true positives per 100 patients relative to the All-patient treatment strategy. Complex models based on machine learning algorithms yielded incrementally better discriminatory power and much improved goodness-of-fitness tests from those based on main effect statistical modeling. This Medicare population represents a highly vulnerable group for incident CVD events. This population would benefit from an integrated approach to their care and management, including attention to their comorbidities and lifestyle factors, as well as medication adherence.

Inclisiran—A Revolutionary Addition to a Cholesterol-Lowering Therapy

Hypercholesterolemia plays a crucial role in the development of atherosclerosis, but it remains an undertreated and underdiagnosed disease. Taking into consideration the high prevalence of lipid disorders, long duration of the asymptomatic course of the disease, life-threatening complications resulting from inaccurate therapy, and stringent treatment goals concerning LDL cholesterol level in the prevention of cardiovascular events, novel lipid-lowering therapies have been introduced in the last few years. In this article, a drug belonging to the group of small interfering RNA (siRNA) called inclisiran is described. It is a novel molecule that increases the number of LDL receptors (LDLRs) on the surface of hepatic cells by preventing the formation of proprotein convertase subtilisin/kexin type 9 (PCSK9) responsible for the degradation of LDLRs. With great potential for lowering plasma LDL cholesterol level, high liver specificity, comfortable dosing regimen, and good tolerance without significant adverse effects, it could play an important part in future hypolipemic therapies.

Regression discontinuity design to evaluate the effect of statins on myocardial infarction in electronic health records

Regression discontinuity design (RDD) is a quasi-experimental method intended for causal inference in observational settings. While RDD is gaining popularity in clinical studies, there are limited real-world studies examining the performance on estimating known trial casual effects. The goal of this paper is to estimate the effect of statins on myocardial infarction (MI) using RDD and compare with propensity score matching and Cox regression. For the RDD, we leveraged a 2008 UK guideline that recommends statins if a patient's 10-year cardiovascular disease (CVD) risk score > 20%. We used UK electronic health record data from the Health Improvement Network on 49,242 patients aged 65 + in 2008-2011 (baseline) without a history of CVD and no statin use in the two years prior to the CVD risk score assessment. Both the regression discontinuity (n = 19,432) and the propensity score matched populations (n = 24,814) demonstrated good balance of confounders. Using RDD, the adjusted point estimate for statins on MI was in the protective direction and similar to the statin effect observed in clinical trials, although the confidence interval included the null (HR = 0.8, 95% CI 0.4, 1.4). Conversely, the adjusted estimates using propensity score matching and Cox regression remained in the harmful direction: HR = 2.42 (95% CI 1.96, 2.99) and 2.51 (2.12, 2.97). RDD appeared superior to other methods in replicating the known protective effect of statins with MI, although precision was poor. Our findings suggest that, when used appropriately, RDD can expand the scope of clinical investigations aimed at causal inference by leveraging treatment rules from everyday clinical practice.

Study protocol of the Berlin Research Initiative for Diagnostics, Genetics and Environmental Factors in Schizophrenia (BRIDGE-S)

BACKGROUND

Large-scale collaborative efforts in the field of psychiatric genetics have made substantial progress in unraveling the biological architecture of schizophrenia (SCZ). Although both genetic and environmental factors are known to play a role in schizophrenia etiology our mechanistic understanding of how they shape risk, resilience and disease trajectories remains limited.

METHODS

Here, we present the study protocol of the Berlin Research Initiative for Diagnostics, Genetic and Environmental Factors of Schizophrenia (BRIDGE-S), which aims to collect a densely phenotyped genetic cohort of 1,000 schizophrenia cases and 1,000 controls. The study's main objectives are to build a resource for i) promoting genetic discoveries and ii) genotype-phenotype associations to infer specific disease subtypes, and iii) exploring gene-environment interactions using polyrisk models. All subjects provide a biological sample for genotyping and complete a core questionnaire capturing a variety of environmental exposures, demographic, psychological and health data. Approximately 50% of individuals in the sample will further undergo a comprehensive clinical and neurocognitive assessment.

DISCUSSION

With BRIDGE-S we created a valuable database to study genomic and environmental contributions to schizophrenia risk, onset, and outcomes. Results of the BRIDGE-S study could yield insights into the etiological mechanisms of schizophrenia that could ultimately inform risk prediction, and early intervention and treatment strategies.

Development and validation of personalised risk prediction models for early detection and diagnosis of primary liver cancer among the English primary care population using the QResearch® database: research protocol and statistical analysis plan

BACKGROUND AND RESEARCH AIM

The incidence and mortality of liver cancer have been increasing in the UK in recent years. However, liver cancer is still under-studied. The Early Detection of Hepatocellular Liver Cancer (DeLIVER-QResearch) project aims to address the research gap and generate new knowledge to improve early detection and diagnosis of primary liver cancer from general practice and at the population level. There are three research objectives: (1) to understand the current epidemiology of primary liver cancer in England, (2) to identify and quantify the symptoms and comorbidities associated with liver cancer, and (3) to develop and validate prediction models for early detection of liver cancer suitable for implementation in clinical settings.

METHODS

This population-based study uses the QResearch® database (version 46) and includes adult patients aged 25-84 years old and without a diagnosis of liver cancer at the cohort entry (study period: 1 January 2008-30 June 2021). The team conducted a literature review (with additional clinical input) to inform the inclusion of variables for data extraction from the QResearch database. A wide range of statistical techniques will be used for the three research objectives, including descriptive statistics, multiple imputation for missing data, conditional logistic regression to investigate the association between the clinical features (symptoms and comorbidities) and the outcome, fractional polynomial terms to explore the non-linear relationship between continuous variables and the outcome, and Cox/competing risk regression for the prediction model. We have a specific focus on the 1-year, 5-year, and 10-year absolute risks of developing liver cancer, as risks at different time points have different clinical implications. The internal-external cross-validation approach will be used, and the discrimination and calibration of the prediction model will be evaluated.

DISCUSSION

The DeLIVER-QResearch project uses large-scale representative population-based data to address the most relevant research questions for early detection and diagnosis of primary liver cancer in England. This project has great potential to inform the national cancer strategic plan and yield substantial public and societal benefits.

Cardiovascular risk prediction: from classical statistical methods to machine learning approaches

Nowadays, cardiovascular risk prediction scores are commonly used in primary prevention settings. Estimating the cardiovascular individual risk is of crucial importance for effective patient management and optimal therapy identification, with relevant consequences on secondary prevention settings. To reach this goal, a plethora of risk scores have been developed in the past, most of them assuming that each cardiovascular risk factor is linearly dependent on the outcome. However, the overall accuracy of these methods often remains insufficient to solve the problem at hand. In this scenario, machine learning techniques have repeatedly proved successful in improving cardiovascular risk predictions, being able to capture the non-linearity present in the data. In this concern, we present a detailed discussion concerning the application of classical versus machine learning-based cardiovascular risk scores in the clinical setting. This review aimed to give an overview of the current risk scores based on classical statistical approaches and machine learning techniques applied to predict the risk of several cardiovascular diseases, comparing them, discussing their similarities and differences, and highlighting their main drawbacks to aid the physician having a more critical understanding of these tools.

The application of arterio-venous ratio (AVR) cut-off values in clinic to stratify cardiovascular risk in patients

INTRODUCTION

Cardiovascular risk calculators are a useful tool for identifying at-risk individuals. There are standardised methods for assessing the retinal microcirculation which alters as a consequence of cardiovascular disease (CVD). This study aimed to explore if a standardised retinal vessel assessment conducted in primary optometric care reflects current cardiovascular risk, as measured using two validated CVD risk calculators (QRISK 2; Mayo Clinic).

METHODS

A total of 120 subjects were included in the analyses. Following a routine eye examination, participants had disc-centred retinal photographs and systemic blood pressure taken. Retinal vessel parameters (central retinal artery and vein equivalent and arterio-venous ratio (AVR)) were calculated using semi-automated software. Participants were then grouped into AVR quintiles as defined by the Atherosclerosis Risk in Communities Study (ARIC). Cardiovascular risk was calculated with the validated QRISK and Mayo Clinic health calculators.

RESULTS

Systolic blood pressure was significantly greater in those with an AVR value falling in the lowest quintile compared to the highest quintile (150.65 mmHg vs. 132.21 mmHg [p = 0.001]). Similarly, CVD risk was significantly higher in those with the lowest AVR compared to the highest (QRISK: 14.28% vs. 9.87% [p = 0.05]; MAYO risk: 36.35% vs. 19.21% [p = 0.01]). Chi squared analyses showed a significant difference in the number of hypertensives in the lowest AVR quintile compared to those in the highest [p = 0.02].

CONCLUSION

Whilst the ARIC population is not directly comparable to the population used to develop the QRISK calculator, it has been shown that its application could help to identify at risk individuals using retinal vessel analyses.

Identifying and managing psoriasis-associated comorbidities: the IMPACT research programme

Background

Psoriasis is a common, lifelong inflammatory skin disease, the severity of which can range from limited disease involving a small body surface area to extensive skin involvement. It is associated with high levels of physical and psychosocial disability and a range of comorbidities, including cardiovascular disease, and it is currently incurable.

Objectives

To (1) confirm which patients with psoriasis are at highest risk of developing additional long-term conditions and identify service use and costs to patient, (2) apply knowledge about risk of comorbid disease to the development of targeted screening services to reduce risk of further disease, (3) learn how patients with psoriasis cope with their condition and about their views of service provision, (4) identify the barriers to provision of best care for patients with psoriasis and (5) develop patient self-management resources and staff training packages to improve the lives of people with psoriasis.

Design

Mixed methods including two systematic reviews, one population cohort study, one primary care screening study, one discrete choice study, four qualitative studies and three mixed-methodology studies.

Setting

Primary care, secondary care and online surveys.

Participants

People with psoriasis and health-care professionals who manage patients with psoriasis.

Results

Prevalence rates for psoriasis vary by geographical location. Incidence in the UK was estimated to be between 1.30% and 2.60%. Knowledge about the cost-effectiveness of therapies is limited because high-quality clinical comparisons of interventions have not been done or involve short-term follow-up. After adjusting for known cardiovascular risk factors, psoriasis (including severe forms) was not found to be an independent risk factor for major cardiovascular events; however, co-occurrence of inflammatory arthritis was a risk factor. Traditional risk factors were high in patients with psoriasis. Large numbers of patients with suboptimal management of known risk factors were found by screening patients in primary care. Risk information was seldom discussed with patients as part of screening consultations, meaning that a traditional screening approach may not be effective in reducing comorbidities associated with psoriasis. Gaps in training of health-care practitioners to manage psoriasis effectively were identified, including knowledge about risk factors for comorbidities and methods of facilitating behavioural change. Theory-based, high-design-quality patient materials broadened patient understanding of psoriasis and self-management. A 1-day training course based on motivational interviewing principles was effective in increasing practitioner knowledge and changing consultation styles. The primary economic analysis indicated a high level of uncertainty. Sensitivity analysis indicated some situations when the interventions may be cost-effective. The interventions need to be assessed for long-term (cost-)effectiveness.

Limitations

The duration of patient follow-up in the study of cardiovascular disease was relatively short; as a result, future studies with longer follow-up are recommended.

Conclusions

Recognition of the nature of the psoriasis and its impact, knowledge of best practice and guideline use are all limited in those most likely to provide care for the majority of patients. Patients and practitioners are likely to benefit from the provision of appropriate support and/or training that broadens understanding of psoriasis as a complex condition and incorporates support for appropriate health behaviour change. Both interventions were feasible and acceptable to patients and practitioners. Cost-effectiveness remains to be explored.

Future work

Patient support materials have been created for patients and NHS providers. A 1-day training programme with training materials for dermatologists, specialist nurses and primary care practitioners has been designed. Spin-off research projects include a national study of responses to psoriasis therapy and a global study of the prevalence and incidence of psoriasis. A new clinical service is being developed locally based on the key findings of the Identification and Management of Psoriasis Associated ComorbidiTy (IMPACT) programme.

Funding

This project was funded by the National Institute for Health Research (NIHR) Programme Grants for Applied Research programme and will be published in full in Programme Grants for Applied Research; Vol. 10, No. 3. See the NIHR Journals Library website for further project information.

Prediction Model Performance With Different Imputation Strategies: A Simulation Study Using a North American ICU Registry

OBJECTIVES

To evaluate the performance of pragmatic imputation approaches when estimating model coefficients using datasets with varying degrees of data missingness.

DESIGN

Performance in predicting observed mortality in a registry dataset was evaluated using simulations of two simple logistic regression models with age-specific criteria for abnormal vital signs (mentation, systolic blood pressure, respiratory rate, WBC count, heart rate, and temperature). Starting with a dataset with complete information, increasing degrees of biased missingness of WBC and mentation were introduced, depending on the values of temperature and systolic blood pressure, respectively. Missing data approaches evaluated included analysis of complete cases only, assuming missing data are normal, and multiple imputation by chained equations. Percent bias and root mean square error, in relation to parameter estimates obtained from the original data, were evaluated as performance indicators.

SETTING

Data were obtained from the Virtual Pediatric Systems, LLC, database (Los Angeles, CA), which provides clinical markers and outcomes in prospectively collected records from 117 PICUs in the United States and Canada.

PATIENTS

Children admitted to a participating PICU in 2017, for whom all required data were available.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Simulations demonstrated that multiple imputation by chained equations is an effective strategy and that even a naive implementation of multiple imputation by chained equations significantly outperforms traditional approaches: the root mean square error for model coefficients was lower using multiple imputation by chained equations in 90 of 99 of all simulations (91%) compared with discarding cases with missing data and lower in 97 of 99 (98%) compared with models assuming missing values are in the normal range. Assuming missing data to be abnormal was inferior to all other approaches.

CONCLUSIONS

Analyses of large observational studies are likely to encounter the issue of missing data, which are likely not missing at random. Researchers should always consider multiple imputation by chained equations (or similar imputation approaches) when encountering even only small proportions of missing data in their work.

Endothelial dysfunction and vascular complications after allogeneic hematopoietic cell transplantation: an expert analysis

Allogeneic hematopoietic cell transplantation (alloHCT) is the standard of care for many diseases. However, survivors often present with serious complications resulting from acute and chronic toxicities and it is crucial to increase consciousness from treating physicians. We performed a comprehensive review of the literature and critically examined recent available data, mostly using the PubMed and Medline search engines for original articles published over the last decade. Better understanding of many alloHCT-related disorders has shown that endothelial injury and vascular damage plays a critical role. The most widely studied endothelial injury syndromes (EIS) are veno-occlusive disease/sinusoidal obstruction syndrome (SOS/VOD), graft-versus-host-disease (GVHD), and transplant-associated thrombotic microangiopathy (TA-TMA). TA-TMA, frequently underdiagnosed, needs to be clarified using certain criteria and, as a life-threatening condition, requires immediate and intensive treatment. The first-in-class complement inhibitor eculizumab has significantly improved outcomes in both the pediatric and adult population. Cardiovascular (CV) events are the second major cause of morbidity and mortality of alloHCT survivors, after GVHD. Long-term monitoring and management of CV risk is expected to also incorporate patient stratification with CV risk prediction models, early markers of vascular dysfunction or procoagulant activity, subclinical target organ damage, arterial stiffness, and subclinical atherosclerosis.

Application of cardiovascular risk scales to identify carotid atherosclerosis in patients with rheumatoid arthritis

Aim. To evaluate the cardiovascular risk (CVR) and analyze its relationship with detection of early carotid artery atherosclerotic lesion in patients with rheumatoid arthritis (RA). Materials and methods. One hundred and nine RA patients aged 45 to 60 without established cardiovascular diseases (CVD) were included in the study. The median age was 52 [48; 54] years, duration of RA was 120 [36; 204] months, DAS28 was 4.7 [3.5; 5.6] points. CVD risk was calculated with mSCORE, Reynolds Risk Score (RRS), ASSIGN, QRISK3, ERS-RA scales and Carotid Artery Doppler Ultrasound Exam was performed for all patients. Results. High risk was found in 5, 5, 14, 6, and 38% of patients according to mSCORE, RRS, ASSIGN, QRISK3, ERS-RA scales, respectively. Atherosclerotic plaques of carotid arteries were found in 30% of patients. It was found that carotid intima-media thickness is correlated to all CVR calculators, age, systolic and diastolic blood pressure, cholesterol, erythrocyte sedimentation rate, interleukin-6 levels. The sensitivity and specificity of the CVR algorithms in prognostication of atherosclerotic carotid artery lesions were 73 and 67% for mSCORE, 64 and 63% for RRS, 64 and 56% for ASSIGN, 73 and 49% for QRISK3, respectively, p0.05 in all cases, 67 and 50% for ERS-RA, p=0.06. Conclusion. RRS, mSCORE, ASSIGN, QRISK3 calculators equally predict atherosclerotic carotid artery damage in RA patients. The optimal ratio of specificity and sensitivity is shown for the mSCORE scale. Stratification of CVR in RA patients should include assessment of the carotid intima-media thickness. To identify CVR in RA patients, the most informative methods are mSCORE calculation and carotid intima-media thickness determination.

Predicting the risk of prostate cancer in asymptomatic men: a cohort study to develop and validate a novel algorithm

Background

Diagnosis of prostate cancer at an early stage can potentially identify tumours when intervention may improve treatment options and survival.

Aim

To develop and validate an equation to predict absolute risk of prostate cancer in asymptomatic men with prostate specific antigen (PSA) tests in primary care.

Design and setting

Cohort study using data from English general practices, held in the QResearch database.

Method

Routine data were collected from 1098 QResearch English general practices linked to mortality, hospital, and cancer records for model development. Two separate sets of practices were used for validation. In total, there were 844 455 men aged 25–84 years with PSA tests recorded who were free of prostate cancer at baseline in the derivation cohort; the validation cohorts comprised 292 084 and 316 583 men. The primary outcome was incident prostate cancer. Cox proportional hazards models were used to derive 10-year risk equations. Measures of performance were determined in both validation cohorts.

Results

There were 40 821 incident cases of prostate cancer in the derivation cohort. The risk equation included PSA level, age, deprivation, ethnicity, smoking status, serious mental illness, diabetes, BMI, and family history of prostate cancer. The risk equation explained 70.4% (95% CI = 69.2 to 71.6) of the variation in time to diagnosis of prostate cancer (R²) (D statistic 3.15, 95% CI = 3.06 to 3.25; Harrell’s C-index 0.917, 95% CI = 0.915 to 0.919). Two-step approach had higher sensitivity than a fixed PSA threshold at identifying prostate cancer cases (identifying 68.2% versus 43.9% of cases), high-grade cancers (49.2% versus 40.3%), and deaths (67.0% versus 31.5%).

Conclusion

The risk equation provided valid measures of absolute risk and had higher sensitivity for incident prostate cancer, high-grade cancers, and prostate cancer mortality than a simple approach based on age and PSA threshold.

Assessing Cardiovascular Risk in Patients with Diabetes: An Update

The globalization of the Western lifestyle has resulted in increase of diabetes mellitus, a complex, multifactorial disease. Diabetes mellitus is a condition often related to the disorders of the cardiovascular system. It is well established that three quarters of diabetics, aged over 40, will die from cardiovascular disease and are more likely than non-diabetics to die from their first cardiovascular event. Therefore, it is of paramount importance to individualize treatment via risk stratification. Conditions that increase cardiovascular risk in people with diabetes include age more than 40 years, male gender, history of relative suffering from premature CHD, blood pressure and high LDL levels, presence of microalbuminuria, obstructive sleepapnea, erectile dysfunction and other conditions.

Several models have been developed in order to assess cardiovascular risk in people with and without diabetes. Some of them have been proven to be inadequate while others are widely used for years. An emerging way of risk assessment in patients with diabetes mellitus is the use of biomarkers but a lot of research needs to be done in this field in order to have solid conclusions.

Systemic Lupus Erythematosus, Its Impact on Selected Cardiovascular Risk Factors, and Correlation with Duration of Illness: A Pilot Study

Systemic lupus erythematosus is a rare autoimmune disease. It leads to an increased production of proinflammatory molecules that accelerates atherogenesis and could cause an endothelium dysfunction. The aim of the study was to assess cardiovascular risk factors such as BMI and lipid profile as well as left ventricular ejection fraction among patients with SLE, and a correlation of these factors with duration of the disease. Materials and Methods. The researched group consisted of patients with SLE, being under control of the outpatient clinic of cardiology. This group included 38 patients among whom 34 were women (56.17 ± 11.05 years) and 4 were men (65.50 ± 9.22 years). The control group consisted of 19 healthy women (53.31 ± 11.94 years) and 2 healthy men (38.51 ± 7.53 years). Measurements were taken in the same conditions by trained medical staff. Results. Excessive body weight (BMI >25 kg/m²) was more frequent in the SLE group, but it was not statistically significant (55.26% vs. 52.38%, p = 0.6159). LVEF values were lower in their searched group, and this factor showed statistical significance (53.92% ± 6.46 vs. 58.67% ± 4.69, p = 0.0044). Thickness of the IMT was higher and statistically important among patients with SLE, both in left (1.22 ± 0.27 mm vs. 0.7 ± 0.21 mm, p = 0.0001) and right common carotid artery (1.16 ± 0.26 mm vs. 0.59 ± 0.15 mm, p = 0.0001), compared to the controls. Conclusions. Patients with SLE are at greater risk of developing cardiovascular diseases as the illness progresses. The activity of the disease according to the SLEDAI-2K scale may have an impact on the LVEF values which was significantly decreased in the group with active disease, but further thorough investigation is required to fully evaluate the impact of individual components of the disease and its treatment on the CVD development and mortality.

Cardiovascular risk factor documentation and management in primary care electronic medical records among people with schizophrenia in Ontario, Canada: retrospective cohort study

OBJECTIVES

In order to address the substantial increased risk of cardiovascular disease among people with schizophrenia, it is necessary to identify the factors responsible for some of that increased risk. We analysed the extent to which these risk factors were documented in primary care electronic medical records (EMR), and compared their documentation by patient and provider characteristics.

DESIGN

Retrospective cohort study.

SETTING

EMR database of the University of Toronto Practice-Based Research Network Data Safe Haven.

PARTICIPANTS

197 129 adults between 40 and 75 years of age; 4882 with schizophrenia and 192 427 without.

PRIMARY AND SECONDARY OUTCOME MEASURES

Documentation of cardiovascular disease risk factors (age, sex, smoking history, presence of diabetes, blood pressure, whether a patient is currently on medication to reduce blood pressure, total cholesterol and high-density lipoprotein cholesterol).

RESULTS

Documentation of cardiovascular risk factors was more complete among people with schizophrenia (74.5% of whom had blood pressure documented at least once in the last 2 years vs 67.3% of those without, p>0.0001). Smoking status was not documented in 19.8% of those with schizophrenia and 20.8% of those without (p=0.0843). Factors associated with improved documentation included older patients (OR for ages 70-75 vs 45-49=3.51, 95% CI 3.26 to 3.78), male patients (OR=1.39, 95% CI 1.33 to 1.45), patients cared for by a female provider (OR=1.52, 95% CI 1.12 to 2.07) and increased number of encounters (OR for ≥10 visits vs 3-5 visits=1.53, 95% CI 1.46 to 1.60).

CONCLUSIONS

Documentation of cardiovascular risk factors was better among people with schizophrenia than without, although overall documentation was inadequate. Efforts to improve documentation of risk factors are warranted in order to facilitate improved management.

Development and Internal Validation of a Model Predicting Premature Cardiovascular Disease Among Women With Hypertensive Disorders of Pregnancy: A Population-Based Study in Quebec, Canada

Background

Hypertensive disorders of pregnancy (HDP) are associated with an increased risk of premature cardiovascular disease (CVD), but existing cardiovascular prediction models do not adequately capture risks in young women. We developed a model to predict the 10‐year risk of premature CVD and mortality among women who have HDP.

Methods and Results

Using a population‐based cohort of women with HDP who delivered between April 1989 and March 2017 in Quebec, Canada, we developed a 10‐year CVD risk model using Cox proportional hazards regression. Women aged 18 to 45 years were followed from their first HDP‐complicated delivery until March 2018. We assessed performance of the model based on discrimination, calibration, and risk stratification ability. Internal validity was assessed using the bootstrap method. The cohort included 95 537 women who contributed 1 401 084 person‐years follow‐up. In total, 4024 (4.2%) of women were hospitalized for CVD, of which 1585 events (1.6%) occurred within 10 years of follow‐up. The final model had modest discriminatory performance (area under the receiver operating characteristic curve, 0.66; 95% CI, 0.65–0.67) and good calibration with slope of 0.95 and intercept of −0.19. There was moderate classification accuracy (likelihood ratio+: 5.90; 95% CI, 5.01–6.95) in the highest‐risk group upon risk stratification.

Conclusions

Overall, our model had modest performance in predicting the 10‐year risk of premature CVD for women with HDP. We recommend the addition of clinical variables, and external validation, before consideration for clinical use.

Association of Low Socioeconomic Status With Premature Coronary Heart Disease in US Adults

Importance

Individuals with low socioeconomic status (SES) bear a disproportionate share of the coronary heart disease (CHD) burden, and CHD remains the leading cause of mortality in low-income US counties.

Objective

To estimate the excess CHD burden among individuals in the United States with low SES and the proportions attributable to traditional risk factors and to other factors associated with low SES.

Design, Setting, and Participants

This computer simulation study used the Cardiovascular Disease Policy Model, a model of CHD and stroke incidence, prevalence, and mortality among adults in the United States, to project the excess burden of early CHD. The proportion of this excess burden attributable to traditional CHD risk factors (smoking, high blood pressure, high low-density lipoprotein cholesterol, low high-density lipoprotein cholesterol, type 2 diabetes, and high body mass index) compared with the proportion attributable to other risk factors associated with low SES was estimated. Model inputs were derived from nationally representative US data and cohort studies of incident CHD. All US adults aged 35 to 64 years, stratified by SES, were included in the simulations.

Exposures

Low SES was defined as income below 150% of the federal poverty level or educational level less than a high school diploma.

Main Outcomes and Measures

Premature (before age 65 years) myocardial infarction (MI) rates and CHD deaths.

Results

Approximately 31.2 million US adults aged 35 to 64 years had low SES, of whom approximately 16 million (51.3%) were women. Compared with individuals with higher SES, both men and women in the low-SES group had double the rate of MIs (men: 34.8 [95% uncertainty interval (UI), 31.0-38.8] vs 17.6 [95% UI, 16.0-18.6]; women: 15.1 [95% UI, 13.4-16.9] vs 6.8 [95% UI, 6.3-7.4]) and CHD deaths (men: 14.3 [95% UI, 13.0-15.7] vs 7.6 [95% UI, 7.3-7.9]; women: 5.6 [95% UI, 5.0-6.2] vs 2.5 [95% UI, 2.3-2.6]) per 10 000 person-years. A higher burden of traditional CHD risk factors in adults with low SES explained 40% of these excess events; the remaining 60% of these events were attributable to other factors associated with low SES. Among a simulated cohort of 1.3 million adults with low SES who were 35 years old in 2015, the model projected that 250 000 individuals (19%) will develop CHD by age 65 years, with 119 000 (48%) of these CHD cases occurring in excess of those expected for individuals with higher SES.

Conclusions and Relevance

This study suggested that, for approximately one-quarter of US adults aged 35 to 64 years, low SES was substantially associated with early CHD burden. Although biomedical interventions to modify traditional risk factors may decrease the disease burden, disparities by SES may remain without addressing SES itself.

Gamma-glutamyl transferase and cardiovascular risk in nonalcoholic fatty liver disease: The Gut and Obesity Asia initiative

BACKGROUND

Gamma-glutamyl transferase (GGT) is associated with the risk of cardiovascular disease (CVD) in the general population.

AIM

To identify the association of baseline GGT level and QRISK2 score among patients with biopsy-proven nonalcoholic fatty liver disease (NAFLD).

METHODS

This was a retrospective study involving 1535 biopsy-proven NAFLD patients from 10 Asian centers in 8 countries using data collected by the Gut and Obesity in Asia (referred to as "GO ASIA") workgroup. All patients with available baseline GGT levels and all 16 variables for the QRISK2 calculation (QRISK2-2017; developed by researchers at the United Kingdom National Health Service; https://qrisk.org/2017/; 10-year cardiovascular risk estimation) were included and compared to healthy controls with the same age, sex, and ethnicity. Relative risk was reported. QRISK2 score > 10% was defined as the high-CVD-risk group. Fibrosis stages 3 and 4 (F3 and F4) were considered advanced fibrosis.

RESULTS

A total of 1122 patients (73%) had complete data and were included in the final analysis; 314 (28%) had advanced fibrosis. The median age (interquartile range [IQR]) of the study population was 53 (44-60) years, 532 (47.4%) were females, and 492 (43.9%) were of Chinese ethnicity. The median 10-year CVD risk (IQR) was 5.9% (2.6-10.9), and the median relative risk of CVD over 10 years (IQR) was 1.65 (1.13-2.2) compared to healthy individuals with the same age, sex, and ethnicity. The high-CVD-risk group was significantly older than the low-risk group (median [IQR]: 63 [59-67] vs 49 [41-55] years; P < 0.001). Higher fibrosis stages in biopsy-proven NAFLD patients brought a significantly higher CVD risk (P < 0.001). Median GGT level was not different between the two groups (GGT [U/L]: Median [IQR], high risk 60 [37-113] vs low risk 66 [38-103], P = 0.56). There was no correlation between baseline GGT level and 10-year CVD risk based on the QRISK2 score (r = 0.02).

CONCLUSION

The CVD risk of NAFLD patients is higher than that of healthy individuals. Baseline GGT level cannot predict CVD risk in NAFLD patients. However, advanced fibrosis is a predictor of a high CVD risk.

Predicted Versus Observed Major Adverse Cardiac Event Risk in Women With Evidence of Ischemia and No Obstructive Coronary Artery Disease: A Report From WISE (Women's Ischemia Syndrome Evaluation)

Background Primary prevention risk scores are commonly used to predict cardiovascular (CVD) outcomes. The applicability of these scores in patients with evidence of myocardial ischemia but no obstructive coronary artery disease is unclear. Methods and Results Among 935 women with signs and symptoms of ischemia enrolled in WISE (Women's Ischemia Syndrome Evaluation), 567 had no obstructive coronary artery disease on angiography. Of these, 433 had had available risk data for 6 commonly used scores: Framingham Risk Score, Reynolds Risk Score, Adult Treatment Panel III, Atherosclerotic Cardiovascular Disease, Systematic Coronary Risk Evaluation, Cardiovascular Risk Score 2. Score-specific CVD rates were assessed. For each score, we evaluated predicted versus observed event rates at 10-year follow-up using c statistic. Recalibration was done for 3 of the 6 scores. The 433 women had a mean age of 56.9±9.4 years, 82.5% were white, 52.7% had hypertension, 43.6% had dyslipidemia, and 16.9% had diabetes mellitus. The observed 10-year score-specific CVD rates varied between 5.54% (Systematic Coronary Risk Evaluation) to 28.87% (Framingham Risk Score), whereas predicted event rates varied from 1.86% (Systematic Coronary Risk Evaluation) to 6.99% (Cardiovascular Risk Score 2). The majority of scores showed moderate discrimination (c statistic 0.53 for Atherosclerotic Cardiovascular Disease and Systematic Coronary Risk Evaluation; 0.78 for Framingham Risk Score) and underestimated risk (statistical discordance -58% for Adult Treatment Panel III; -84% for Atherosclerotic Cardiovascular Disease). Recalibrated Reynolds Risk Score, Atherosclerotic Cardiovascular Disease, and Framingham Risk Score had improved performance, but significant underestimation remained. Conclusions Commonly used CVD risk scores fail to accurately predict CVD rates in women with ischemia and no obstructive coronary artery disease. These results emphasize the need for new risk assessment scores to reliably assess this population.

Understanding the links between cardiovascular disease and Parkinson's disease

Studies investigating the associations between genetic or environmental factors and Parkinson's disease (PD) have uncovered a number of factors shared with cardiovascular disease, either as risk factors or manifestations of cardiovascular disease itself. Older age, male sex, and possibly type 2 diabetes are examples. On the other hand, coffee consumption and physical activity are each associated with a lower risk of both PD and cardiovascular disease. This observation raises questions about the underlying pathophysiological links between cardiovascular disease and PD. There is evidence for common mechanisms in the areas of glucose metabolism, cellular stress, lipid metabolism, and inflammation. On the other hand, smoking and total/low-density lipoprotein cholesterol appear to have opposite associations with cardiovascular disease and PD. Thus, it is uncertain whether the treatment of cardiovascular risk factors will impact on the onset or progression of PD. The available data suggest that a nuanced approach is necessary to manage risk factors such as cholesterol levels once the associations are better understood. Ultimately, the choice of therapy may be tailored to a patient's comorbidity profile. This review presents the epidemiological evidence for both concordant and discordant associations between cardiovascular disease and PD, discusses the cellular and metabolic processes that may underlie these links, and explores the implications this has for patient care and future research. © 2019 International Parkinson and Movement Disorder Society.

Strengthening Referral Networks for Management of Hypertension Across the Health System (STRENGTHS) in western Kenya: a study protocol of a cluster randomized trial

Background

Hypertension is a major risk factor for cardiovascular disease (CVD), yet treatment and control rates for hypertension are very low in low- and middle-income countries (LMICs). Lack of effective referral networks between different levels of the health system is one factor that threatens the ability to achieve adequate blood pressure control and prevent CVD-related morbidity. Health information technology and peer support are two strategies that have improved care coordination and clinical outcomes for other disease entities in other settings; however, their effectiveness and cost-effectiveness in strengthening referral networks to improve blood pressure control and reduce CVD risk in low-resource settings are unknown.

Methods/design

We will use the PRECEDE-PROCEED framework to conduct transdisciplinary implementation research, focused on strengthening referral networks for hypertension in western Kenya. We will conduct a baseline needs and contextual assessment using a mixed-methods approach, in order to inform a participatory, community-based design process to fully develop a contextually and culturally appropriate intervention model that combines health information technology and peer support. Subsequently, we will conduct a two-arm cluster randomized trial comparing 1) usual care for referrals vs 2) referral networks strengthened with our intervention. The primary outcome will be one-year change in systolic blood pressure. The key secondary clinical outcome will be CVD risk reduction, and the key secondary implementation outcomes will include referral process metrics such as referral appropriateness and completion rates. We will conduct a mediation analysis to evaluate the influence of changes in referral network characteristics on intervention outcomes, a moderation analysis to evaluate the influence of baseline referral network characteristics on the effectiveness of the intervention, as well as a process evaluation using the Saunders framework. Finally, we will analyze the incremental cost-effectiveness of the intervention relative to usual care, in terms of costs per unit decrease in systolic blood pressure, per percentage change in CVD risk score, and per disability-adjusted life year saved.

Discussion

This study will provide evidence for the implementation of innovative strategies for strengthening referral networks to improve hypertension control in LMICs. If effective, it has the potential to be a scalable model for health systems strengthening in other low-resource settings worldwide.

Trial registration

Clinicaltrials.gov, NCT03543787. Registered on 29 June 2018.

Electronic supplementary material

The online version of this article (10.1186/s13063-019-3661-4) contains supplementary material, which is available to authorized users.

Early Prediction of Cardiovascular Risk after Hematopoietic Cell Transplantation: Are We There Yet?

Cardiovascular (CV) events have emerged as a major cause of morbidity and mortality among hematopoietic cell transplantation (HCT) survivors. Accumulating evidence supports the presence of increased CV risk in HCT recipients. Most studies have focused mainly on traditional CV risk factors, such as the metabolic syndrome and hypertension. However, detection of these factors suggests the development of irreversible overt clinical atherosclerosis. Therefore, earlier prediction of CV risk is needed to prevent CV morbidity and mortality in these patients. In the field of CV research, endothelial dysfunction is considered an early event in the pathophysiology of CV risk factors, and a number of markers have been proposed for its assessment. In addition, markers of subclinical target organ damage have been introduced to implement CV risk prediction and early preventive or intensive therapeutic interventions. Furthermore, a number of CV models have been suggested aiming for optimal stratification of patients. Preliminary studies have indicated excess CV risk using these early markers in HCT recipients. However, their role in the pathophysiology and clinical practice in HCT survivors remains largely understudied. Taking into account the need for increased awareness from treating physicians in this evolving setting, we conducted a state-of-the-art review aiming to summarize current knowledge on endothelial dysfunction, subclinical target organ damage, and CV risk prediction in HCT survivors.

Sex Differences in the Assessment of Cardiovascular Risk in Primary Health Care: A Systematic Review

OBJECTIVE

To determine whether sex differences exist in the assessment of cardiovascular disease (CVD) risk scores/risk factors in primary health care.

DESIGN/METHODS

PubMed and EMBASE were systematically searched on 31 January 2017. Clinical trials and observational studies were included if they reported on the assessment of CVD risk score, blood pressure (BP), cholesterol or smoking status in primary health care, stratified by sex. Meta-analyses were performed, using random effects models, to determine differences between sexes, separately for adjusted and unadjusted data.

RESULTS

Of 14,928 studies found in the search, 22 studies (including 4,754,782 patients) were included in the systematic review with the meta-analysis for quantitative assessment. Overall, the assessment rates of CVD risk score and risk factors were similar in women and men (CVD risk score: 30.7% vs. 35.2% [difference (95% CI): -4.5 (-5.1, -3.9)]; BP: 91.3% vs. 88.5% [2.8 (2.5, 3.0)]; cholesterol: 69.9% vs. 71.0% [-1.1 (-1.5, -0.8)]; and smoking: 85.9% vs. 86.7% [-0.8 (-1.1, -0.5)]). The pooled, adjusted likelihood of having the risk score, BP and cholesterol assessments were comparable between women and men: OR (95% CI): 0.87 (0.70, 1.07); 1.41 (0.89, 2.25); and 1.15 (0.82, 1.60), respectively. However, women were 32% less likely to be assessed for smoking (0.68 [0.47, 1.00]). There was substantial heterogeneity between studies and the risk of publication bias was moderate.

CONCLUSION

Despite the guideline recommendations, assessment of CVD risk score in primary health care was low in both sexes. Further, women were less likely to be assessed for their smoking status than men, whereas no sex discrepancies were found for BP and cholesterol assessments.

Cardiovascular risk assessments at occupational health services: employee experiences

BACKGROUND

Across England in the UK, population screening for cardiovascular disease (CVD) primarily takes place within general practice in the form of the National Health Service Health Check. Additional screening sites such as occupational health are advocated to improve the population impact.

AIMS

To investigate participant experiences with cardiovascular and type 2 diabetes risk assessment (RA) at occupational health and subsequent support-seeking at general practice.

METHODS

Face-to-face interviews were conducted for this qualitative study. Participants were recruited at three workplaces; a steel works and two hospital sites. Using interpretive phenomenological analyses, themes were drawn from salient narratives and categorically organized.

RESULTS

There were 29 participants. Themes (n = 16) were organized into two domains; factors that facilitated (n = 9) or thwarted (n = 7) participant engagement with the RA and general practice. All participants described the RA as worthwhile and strongly valued RA at occupational health. Those with obesity and high CVD risk highlighted their difficulties in making lifestyle changes. Participants reported confusion and anxiety when GP advice about medication appeared to contradict what participants had interpreted during RA at occupational health.

CONCLUSIONS

This study highlights factors that facilitate or thwart engagement in cardiovascular RA at occupational health services and general practice follow-up. Stakeholders can integrate these factors into standard operating procedures to enhance participant engagement and enable safeguards that minimize potential harm to participants.

Proactive approaches to identifying dementia and dementia risk; a qualitative study of public attitudes and preferences

OBJECTIVES

The aim of this study was to critically explore the views of the public about the acceptability and feasibility of proactive approaches to earlier dementia diagnosis and also identification of people at high risk of dementia.

DESIGN

Qualitative study using task group methodology and thematic data analysis.

SETTING

Task groups were held either at the university (n=5) or at a carers' centre (n=1).

PARTICIPANTS

A convenience sample of 31 of 54 participants identified by local non-statutory agencies took part in a task group. All were aged between 40 years and 80 years, 21 were women and 10men participated.

RESULTS

Despite the use of task group methodology, participants expressed limited understandings of dementia and confusion between proactive approaches. Nevertheless, they highlighted a range of potential benefits and limitations of proactive approaches and the ethical issues raised. There was a preference to embed risk assessment within routine health checks, which focused on achieving a healthier lifestyle, rather than specifically on dementia. Participants emphasised the need to ensure informed consent prior to use of proactive approaches and to provide appropriate support. They also suggested alternative approaches that could potentially facilitate the early detection of dementia or reduce risk at a population level.

CONCLUSIONS

As international policy on dementia shifts towards a prevention agenda there is growing interest in identifying those at risk of developing dementia. This study provides useful insights into the acceptability of the use of such proactive approaches among the public. The introduction of proactive approaches to dementia identification raises complex practical and ethical issues, particularly in the context of low public understanding of dementia. The importance of better quality information about dementia (and the likelihood of developing dementia) and provision of psychological support for those undergoing risk assessment were highlighted.

Statin initiations and QRISK2 scoring in UK general practice: a THIN database study

BACKGROUND

Statin prescribing should be based on cardiovascular disease (CVD) risk, but evidence suggests overtreatment of low-risk groups and undertreatment of high-risk groups.

AIM

To investigate the relationship between CVD risk scoring in primary care and initiation of statins for the primary prevention of CVD, and the effect of changes to the National Institute for Health and Care Excellence (NICE) guidance in 2014.

DESIGN AND SETTING

Historical cohort study using UK electronic primary care records.

METHOD

A cohort was created of statin-naïve patients without CVD between 1 January 2000 and 31 December 2015. CVD risk scores (calculated using QRISK2 available from 2012) and statin initiations were identified. Rates of CVD risk score recording were calculated and relationships between CVD risk category (low-, intermediate-, and high-risk: <10%, 10-19.9%, and ≥20% 10-year CVD risk) and statin initiation were analysed.

RESULTS

A total of 1.4 million patients were identified from 248 practices. Of these, 151 788 had a recorded CVD risk score since 2012 (10.67%) and 217 860 were initiated on a statin (15.31%). Among patients initiated on a statin after 2012, 27.1% had a documented QRISK2 score: 2.7% of low-risk, 13.8% of intermediate-risk, and 35.0% of high-risk patients were initiated on statins. Statin initiation rates halved from a peak in 2006. After the 2014 NICE guidelines, statin initiation rates declined in high-risk patients but increased in intermediate-risk patients.

CONCLUSION

Most patients initiated on statins had no QRISK2 score recorded. Most patients at high risk of CVD were not initiated on statins. One in six statin initiations were to low-risk patients indicating significant overtreatment. Initiations of statins in intermediate-risk patients rose after NICE guidelines were updated in 2014.

Development and validation of QDiabetes-2018 risk prediction algorithm to estimate future risk of type 2 diabetes: cohort study

Objectives To derive and validate updated QDiabetes-2018 prediction algorithms to estimate the 10 year risk of type 2 diabetes in men and women, taking account of potential new risk factors, and to compare their performance with current approaches.Design Prospective open cohort study.Setting Routinely collected data from 1457 general practices in England contributing to the QResearch database: 1094 were used to develop the scores and a separate set of 363 were used to validate the scores.Participants 11.5 million people aged 25-84 and free of diabetes at baseline: 8.87 million in the derivation cohort and 2.63 million in the validation cohort.Methods Cox proportional hazards models were used in the derivation cohort to derive separate risk equations in men and women for evaluation at 10 years. Risk factors considered included those already in QDiabetes (age, ethnicity, deprivation, body mass index, smoking, family history of diabetes in a first degree relative, cardiovascular disease, treated hypertension, and regular use of corticosteroids) and new risk factors: atypical antipsychotics, statins, schizophrenia or bipolar affective disorder, learning disability, gestational diabetes, and polycystic ovary syndrome. Additional models included fasting blood glucose and glycated haemoglobin (HBA1c). Measures of calibration and discrimination were determined in the validation cohort for men and women separately and for individual subgroups by age group, ethnicity, and baseline disease status.Main outcome measure Incident type 2 diabetes recorded on the general practice record.Results In the derivation cohort, 178 314 incident cases of type 2 diabetes were identified during follow-up arising from 42.72 million person years of observation. In the validation cohort, 62 326 incident cases of type 2 diabetes were identified from 14.32 million person years of observation. All new risk factors considered met our model inclusion criteria. Model A included age, ethnicity, deprivation, body mass index, smoking, family history of diabetes in a first degree relative, cardiovascular disease, treated hypertension, and regular use of corticosteroids, and new risk factors: atypical antipsychotics, statins, schizophrenia or bipolar affective disorder, learning disability, and gestational diabetes and polycystic ovary syndrome in women. Model B included the same variables as model A plus fasting blood glucose. Model C included HBA1c instead of fasting blood glucose. All three models had good calibration and high levels of explained variation and discrimination. In women, model B explained 63.3% of the variation in time to diagnosis of type 2 diabetes (R²), the D statistic was 2.69 and the Harrell's C statistic value was 0.89. The corresponding values for men were 58.4%, 2.42, and 0.87. Model B also had the highest sensitivity compared with current recommended practice in the National Health Service based on bands of either fasting blood glucose or HBA1c. However, only 16% of patients had complete data for blood glucose measurements, smoking, and body mass index.Conclusions Three updated QDiabetes risk models to quantify the absolute risk of type 2 diabetes were developed and validated: model A does not require a blood test and can be used to identify patients for fasting blood glucose (model B) or HBA1c (model C) testing. Model B had the best performance for predicting 10 year risk of type 2 diabetes to identify those who need interventions and more intensive follow-up, improving on current approaches. Additional external validation of models B and C in datasets with more completely collected data on blood glucose would be valuable before the models are used in clinical practice.

Use of Repeated Blood Pressure and Cholesterol Measurements to Improve Cardiovascular Disease Risk Prediction: An Individual-Participant-Data Meta-Analysis

The added value of incorporating information from repeated blood pressure and cholesterol measurements to predict cardiovascular disease (CVD) risk has not been rigorously assessed. We used data on 191,445 adults from the Emerging Risk Factors Collaboration (38 cohorts from 17 countries with data encompassing 1962-2014) with more than 1 million measurements of systolic blood pressure, total cholesterol, and high-density lipoprotein cholesterol. Over a median 12 years of follow-up, 21,170 CVD events occurred. Risk prediction models using cumulative mean values of repeated measurements and summary measures from longitudinal modeling of the repeated measurements were compared with models using measurements from a single time point. Risk discrimination (C-index) and net reclassification were calculated, and changes in C-indices were meta-analyzed across studies. Compared with the single-time-point model, the cumulative means and longitudinal models increased the C-index by 0.0040 (95% confidence interval (CI): 0.0023, 0.0057) and 0.0023 (95% CI: 0.0005, 0.0042), respectively. Reclassification was also improved in both models; compared with the single-time-point model, overall net reclassification improvements were 0.0369 (95% CI: 0.0303, 0.0436) for the cumulative-means model and 0.0177 (95% CI: 0.0110, 0.0243) for the longitudinal model. In conclusion, incorporating repeated measurements of blood pressure and cholesterol into CVD risk prediction models slightly improves risk prediction.

Development and validation of QMortality risk prediction algorithm to estimate short term risk of death and assess frailty: cohort study

Objectives To derive and validate a risk prediction equation to estimate the short term risk of death, and to develop a classification method for frailty based on risk of death and risk of unplanned hospital admission.Design Prospective open cohort study.Participants Routinely collected data from 1436 general practices contributing data to QResearch in England between 2012 and 2016. 1079 practices were used to develop the scores and a separate set of 357 practices to validate the scores. 1.47 million patients aged 65-100 years were in the derivation cohort and 0.50 million patients in the validation cohort.Methods Cox proportional hazards models in the derivation cohort were used to derive separate risk equations in men and women for evaluation of the risk of death at one year. Risk factors considered were age, sex, ethnicity, deprivation, smoking status, alcohol intake, body mass index, medical conditions, specific drugs, social factors, and results of recent investigations. Measures of calibration and discrimination were determined in the validation cohort for men and women separately and for each age and ethnic group. The new mortality equation was used in conjunction with the existing QAdmissions equation (which predicts risk of unplanned hospital admission) to classify patients into frailty groups.Main outcome measure The primary outcome was all cause mortality.Results During follow-up 180 132 deaths were identified in the derivation cohort arising from 4.39 million person years of observation. The final model included terms for age, body mass index, Townsend score, ethnic group, smoking status, alcohol intake, unplanned hospital admissions in the past 12 months, atrial fibrillation, antipsychotics, cancer, asthma or chronic obstructive pulmonary disease, living in a care home, congestive heart failure, corticosteroids, cardiovascular disease, dementia, epilepsy, learning disability, leg ulcer, chronic liver disease or pancreatitis, Parkinson's disease, poor mobility, rheumatoid arthritis, chronic kidney disease, type 1 diabetes, type 2 diabetes, venous thromboembolism, anaemia, abnormal liver function test result, high platelet count, visited doctor in the past year with either appetite loss, unexpected weight loss, or breathlessness. The model had good calibration and high levels of explained variation and discrimination. In women, the equation explained 55.6% of the variation in time to death (R²), and had very good discrimination-the D statistic was 2.29, and Harrell's C statistic value was 0.85. The corresponding values for men were 53.1%, 2.18, and 0.84. By combining predicted risks of mortality and unplanned hospital admissions, 2.7% of patients (n=13 665) were classified as severely frail, 9.4% (n=46 770) as moderately frail, 43.1% (n=215 253) as mildly frail, and 44.8% (n=223 790) as fit.Conclusions We have developed new equations to predict the short term risk of death in men and women aged 65 or more, taking account of demographic, social, and clinical variables. The equations had good performance on a separate validation cohort. The QMortality equations can be used in conjunction with the QAdmissions equations, to classify patients into four frailty groups (known as QFrailty categories) to enable patients to be identified for further assessment or interventions.

[Characteristics and cardiovascular events in a general population included in the RICARTO (RIesgo CARdiovascular TOledo) study: Data from the first 1,500 individuals included in the study]

INTRODUCTION

The aim of this study was to assess cardiovascular risk (CVR) by investigating the prevalence of CVR factors (CVRF), target organ damage (TOD), and cardiovascular disease (CVD) in general population of the health area of Toledo, Spain.

MATERIAL AND METHODS

Epidemiological and observational study that analysed a sample from the general population aged 18years or older, randomly selected from a database of health cards stratified by age and gender. Clinical history, physical examination, and complementary tests were performed. Total blood and serum samples were frozen at -85°C to evaluate genetic studies in the future. Standard statistical analysis was performed. CVR was assessed by the SCORE scale calibrated for the Spanish population, and the Framingham Heart Study scale.

RESULTS

A total of 1,500 individuals (mean age 49.1±15.8years, 55.6% women) were included. Prevalences: dyslipidaemia 56.9% (95% confidence interval [95% CI]: 54.3-59.4), hypertension 33.0% (95%CI: 30.6-35.4), diabetes mellitus 8.6% (95%CI: 7.17-10.1), smoking 24.2% (95%CI; 122.0-26.4), obesity 25.3% (95%CI; 23.1-27.5), and sedentary life-style 39.4% (95%CI; 36.9-41.8). No CVRF was reported in 21.1% of cases, and 18.6% had 3-5 CVRF. TOD: electrocardiographic left ventricular hypertrophy, 4.3%, peripheral artery disease, 10.1% (Doppler ultrasound), and 15.3% (oscillometric device), microalbuminuria, 4.3%, sub-clinical renal disease, 3.2%, and nephropathy in 3.8% (CKD-EPI). At least one CVD was reported in 9.2% of cases. A low CVR (SCORE) was present in 44.6% of individuals.

CONCLUSIONS

Dyslipidaemia was found in 60% of individuals, 40% had a sedentary life-style, 30% with hypertension, 20% smoked, 20% obesity, and almost 10% with diabetes. More than a half of individuals have a moderate-high-very high risk. The prevalence of TOD and CVD are significant.

Comparison of cardiovascular risk algorithms in patients with vs without rheumatoid arthritis and the role of C-reactive protein in predicting cardiovascular outcomes in rheumatoid arthritis

Objectives

The aims were to compare the performance of cardiovascular risk calculators, Framingham Risk Score (FRS) and QRISK2, in RA and matched non-RA patients and to evaluate whether their performance could be enhanced by the addition of CRP.

Methods

We conducted a retrospective analysis, using a clinical practice data set linked to Hospital Episode Statistics (HES) data from the UK. Patients presenting with at least one RA diagnosis code and no prior cardiovascular events were matched to non-RA patients using disease risk scores. The overall performance of the FRS and QRISK2 was compared between cohorts, and assessed with and without CRP in the RA cohort using C-Index, Akaike Information Criterion (AIC) and the net reclassification index (NRI).

Results

Four thousand seven hundred and eighty RA patients met the inclusion criteria and were followed for a mean of 3.8 years. The C-Index for the FRS in the non-RA and RA cohort was 0.783 and 0.754 (P < 0.001) and that of the QRISK2 was 0.770 and 0.744 (P < 0.001), respectively. Log[CRP] was positively associated with cardiovascular events, but improvements in the FRS and QRISK2 C-Indices as a result of inclusion of CRP were small, from 0.764 to 0.767 (P = 0.026) for FRS and from 0.764 to 0.765 (P = 0.250) for QRISK2. The NRI was 3.2% (95% CI: -2.8, 5.7%) for FRS and -2.0% (95% CI: -5.8, 4.5%) for QRISK2.

Conclusion

The C-Index for the FRS and QRISK2 was significantly better in the non-RA compared with RA patients. The addition of CRP in both equations was not associated with a significant improvement in reclassification based on NRI.

[Cardiovascular risk and cardiovascular events in the general population of the sanitary area of Toledo. RICARTO Study]

INTRODUCTION

The main aim of this study is to ascertain the prevalence of cardiovascular risk factors (CVRF), target organ damage (TOD), cardiovascular disease (CVD), as well as life habits (physical exercise, alcohol consumption, and Mediterranean diet) in the population of a Health Area in Toledo, Spain, to assess cardiovascular risk (CVR).

MATERIAL AND METHODS

Epidemiological and observational study that will analyse a sample from the general population aged 18 years or older, randomly selected from a database of health cards, and stratified by age and gender. Clinical history, physical examination, and complementary tests will be performed. Aliquots of whole blood and serum samples will be stored at a temperature of-85°C to evaluate future genetic studies. CVR will be estimated by using SCORE project scales calibrated for Spanish population and the Framingham Heart Study scale. When the estimated sample size has been achieved and after a minimum follow-up of 5 years, a final visit will performed in which CVRF, TOD, CVD, CVRF control, and fatal and non-fatal outcomes will be evaluated.

DISCUSSION

The RICARTO study is aimed to assess the prevalence of the main CVRF, TOD and CVD in order to determine the CVR in the general population of a health area of Toledo. An analysis will be repeated on the final sample after at least 5 years of follow-up to ascertain the incidence of CV outcomes and the temporal trends of life style, as well as the prevalence of CVRF, TOD, and CVD.

Development and validation of QRISK3 risk prediction algorithms to estimate future risk of cardiovascular disease: prospective cohort study

Objectives To develop and validate updated QRISK3 prediction algorithms to estimate the 10 year risk of cardiovascular disease in women and men accounting for potential new risk factors.Design Prospective open cohort study.Setting General practices in England providing data for the QResearch database.Participants 1309 QResearch general practices in England: 981 practices were used to develop the scores and a separate set of 328 practices were used to validate the scores. 7.89 million patients aged 25-84 years were in the derivation cohort and 2.67 million patients in the validation cohort. Patients were free of cardiovascular disease and not prescribed statins at baseline.Methods Cox proportional hazards models in the derivation cohort to derive separate risk equations in men and women for evaluation at 10 years. Risk factors considered included those already in QRISK2 (age, ethnicity, deprivation, systolic blood pressure, body mass index, total cholesterol: high density lipoprotein cholesterol ratio, smoking, family history of coronary heart disease in a first degree relative aged less than 60 years, type 1 diabetes, type 2 diabetes, treated hypertension, rheumatoid arthritis, atrial fibrillation, chronic kidney disease (stage 4 or 5)) and new risk factors (chronic kidney disease (stage 3, 4, or 5), a measure of systolic blood pressure variability (standard deviation of repeated measures), migraine, corticosteroids, systemic lupus erythematosus (SLE), atypical antipsychotics, severe mental illness, and HIV/AIDs). We also considered erectile dysfunction diagnosis or treatment in men. Measures of calibration and discrimination were determined in the validation cohort for men and women separately and for individual subgroups by age group, ethnicity, and baseline disease status.Main outcome measures Incident cardiovascular disease recorded on any of the following three linked data sources: general practice, mortality, or hospital admission records.Results 363 565 incident cases of cardiovascular disease were identified in the derivation cohort during follow-up arising from 50.8 million person years of observation. All new risk factors considered met the model inclusion criteria except for HIV/AIDS, which was not statistically significant. The models had good calibration and high levels of explained variation and discrimination. In women, the algorithm explained 59.6% of the variation in time to diagnosis of cardiovascular disease (R², with higher values indicating more variation), and the D statistic was 2.48 and Harrell's C statistic was 0.88 (both measures of discrimination, with higher values indicating better discrimination). The corresponding values for men were 54.8%, 2.26, and 0.86. Overall performance of the updated QRISK3 algorithms was similar to the QRISK2 algorithms.Conclusion Updated QRISK3 risk prediction models were developed and validated. The inclusion of additional clinical variables in QRISK3 (chronic kidney disease, a measure of systolic blood pressure variability (standard deviation of repeated measures), migraine, corticosteroids, SLE, atypical antipsychotics, severe mental illness, and erectile dysfunction) can help enable doctors to identify those at most risk of heart disease and stroke.

Neighborhood socioeconomic status at the age of 40 years and ischemic stroke before the age of 50 years: A nationwide cohort study from Sweden

Objective We aimed to study the association between neighborhood socioeconomic status at the age of 40 years and risk of ischemic stroke before the age of 50 years. Methods All individuals in Sweden were included if their 40th birthday occurred between 1998 and 2010. National registers were used to categorize neighborhood socioeconomic status into high, middle, and low and to retrieve information on incident ischemic strokes. Hazard ratios and their 95% confidence intervals were estimated. Results A total of 1,153,451 adults (women 48.9%) were followed for a mean of 5.5 years (SD 3.5 years), during which 1777 (0.30%) strokes among men and 1374 (0.24%) strokes among women were recorded. After adjustment for sex, marital status, education level, immigrant status, region of residence, and neighborhood services, there was a lower risk of stroke in residents from high-socioeconomic status neighborhoods (hazard ratio 0.87, 95% confidence interval 0.78-0.96), and an increased risk of stroke in adults from low-socioeconomic status neighborhoods (hazard ratio 1.16, 95% confidence interval 1.06-1.27), compared to their counterparts living in middle-socioeconomic status neighborhoods. After further adjustment for hospital diagnoses of hypertension, diabetes, heart failure, and atrial fibrillation prior to the age of 40, the higher risk in neighborhoods with low socioeconomic status was attenuated, but remained significant (hazard ratio 1.12, 95% confidence interval 1.02-1.23). Conclusions In a nationwide study of individuals between 40 and 50 years, we found that the risk of ischemic stroke differed depending on neighborhood socioeconomic status, which calls for increased efforts to prevent cardiovascular diseases in low socioeconomic status neighborhoods.

Performance of the Atherosclerotic Cardiovascular Disease Pooled Cohort Risk Equations by Social Deprivation Status

BACKGROUND

The atherosclerosis cardiovascular disease (ASCVD) Pooled Cohort risk equations have shown different calibration across US populations with varied levels of social deprivation.

METHODS AND RESULTS

We analyzed the calibration and discrimination of the Pooled Cohort risk equations by social deprivation status among 9066 REGARDS (REasons for Geographic And Racial Differences in Stroke) study participants not taking statins for whom ASCVD risk may lead to statin initiation. Patients were aged 45 to 79 years, had no ASCVD or diabetes mellitus, and had a low-density lipoprotein cholesterol level 70 to 189 mg/dL. Social deprivation was defined using 3 indicators: annual household income <$25 000, less than a high school education, and living without a partner. At baseline in 2003-2007, 54.6%, 27.4%, and 18.0% of participants had 0, 1, and 2 or 3 indicators showing deprivation, respectively. From baseline through December 2012, 457 participants developed ASCVD (nonfatal/fatal stroke, myocardial infarction, or coronary heart disease death). Predicted and observed ASCVD incidence per 1000 person-years were 8.02 and 6.23 (95% CI, 5.31-7.31), respectively, among participants with 0 indicators of deprivation (Hosmer-Lemeshow P=0.01); 8.05 and 6.61 (95% CI, 5.29-8.24), respectively, with 1 indicator (P=0.09); and 9.83 and 11.40 (95% CI, 9.23-14.05), respectively, with 2 or 3 indicators (P=0.12). The C-index (95% CI) was 0.72 (0.69-0.75), 0.73 (0.69-0.78), and 0.70 (0.65-0.75) among participants with 0, 1, and 2 or 3 indicators of deprivation, respectively. The net reclassification improvement after adding deprivation data to the Pooled Cohort risk equations was modest (0.12; 95% CI, 0.03-0.21).

CONCLUSIONS

The Pooled Cohort risk equations have good calibration among individuals with social deprivation but overestimate ASCVD risk among those with less social deprivation.

A Convolutional Neural Network for Automatic Characterization of Plaque Composition in Carotid Ultrasound

Characterization of carotid plaque composition, more specifically the amount of lipid core, fibrous tissue, and calcified tissue, is an important task for the identification of plaques that are prone to rupture, and thus for early risk estimation of cardiovascular and cerebrovascular events. Due to its low costs and wide availability, carotid ultrasound has the potential to become the modality of choice for plaque characterization in clinical practice. However, its significant image noise, coupled with the small size of the plaques and their complex appearance, makes it difficult for automated techniques to discriminate between the different plaque constituents. In this paper, we propose to address this challenging problem by exploiting the unique capabilities of the emerging deep learning framework. More specifically, and unlike existing works which require a priori definition of specific imaging features or thresholding values, we propose to build a convolutional neural network (CNN) that will automatically extract from the images the information that is optimal for the identification of the different plaque constituents. We used approximately 90 000 patches extracted from a database of images and corresponding expert plaque characterizations to train and to validate the proposed CNN. The results of cross-validation experiments show a correlation of about 0.90 with the clinical assessment for the estimation of lipid core, fibrous cap, and calcified tissue areas, indicating the potential of deep learning for the challenging task of automatic characterization of plaque composition in carotid ultrasound.

Cohort study investigating the relationship between cholesterol, cardiovascular risk score and the prescribing of statins in UK primary care: study protocol

INTRODUCTION

Risk scoring is an integral part of the prevention of cardiovascular disease (CVD) and should form the basis for the decision to offer medication to reduce cholesterol (statins). However, there is a suggestion in the literature that many patients are still initiated on statins based on raised cholesterol rather than a raised CVD risk. It is important, therefore, to investigate the role that lipid levels and CVD risks have in the decision to prescribe. This research will establish how cholesterol levels and CVD risk independently influence the prescribing of statins for the primary prevention of CVD in primary care.

METHODS AND ANALYSIS

The Health Improvement Network (THIN) is a database of coded primary care electronic patient records from over 500 UK general practices. From this resource, a historical cohort will be created of patients without a diagnosis of CVD, not currently receiving a prescription for statins and who had a lipid profile measured. A post hoc QRISK2 score will be calculated for these patients and they will be followed up for 60 days to establish whether they were subsequently prescribed a statin. Primary analysis will consist of predictive modelling using multivariate logistic regression with potential predictors including cholesterol level, calculated QRISK2 score, sociodemographic characteristic and comorbidities. Descriptive statistics will be used to identify trends in prescribing and further secondary analysis will explore what other factors may have influenced the prescribing of statins and the degree of interprescriber variability.

ETHICS AND DISSEMINATION

The THIN Data Collection Scheme was approved by the South-East Multicentre Research Ethics Committee in 2003. Individual studies using THIN require Scientific Review Committee approval. The original protocol for this study and a subsequent amendment have been approved (16THIN009A1). The results will be published in a peer review journal and presented at national and international conferences.

Cohort profile: Women's Healthy Ageing Project (WHAP) - a longitudinal prospective study of Australian women since 1990

Background

The cohort was commenced to examine women’s health from midlife (45–55 years) before the menopausal transition and into ageing.

Methods

Randomised selection and assessment of 2,001 women living in the Melbourne metropolitan area was conducted by the Roy Morgan Centre in 1990/91. Of the 779 women who met the entry criteria for the longitudinal follow-up (aged 45–55 years, menstruating, having a uterus and at least one ovary and not taking hormone therapy) 438 agreed to be seen annually across the menopausal transition from 1992 to 1999. Longitudinal prospective follow-up since 2000 has continued intermittently (2002/03, 2004/05, 2012/13, 2014/15). Data collection has included fasting biomarkers in each year since 1992, clinical assessment, lifestyle and quality of life data, physical measures and validated questionnaire data. Participants have consented to data linkage and, to date, mammogram and BioGrid data have been accessed. Biobank storage including serum, deoxyribonucleic acid (DNA) storage and PAXgene tubes are maintained.

Discussion

The WHAP has contributed to over 200 published research findings, several books, and book chapters in a variety of areas, including: health and wellbeing; mental and cognitive health; bone health; lifestyle, vascular risk and prevention; women’s health and hormonal transition; and cross-cultural research.

With all participants now aged over 70 years, the cohort is ideally placed to answer key questions of healthy ageing in women. With more than 25 years of longitudinal prospective follow-up this Australian dataset is unique in its duration, breadth and detail of measures including clinical review and specialized disease-specific testing and biomarkers. Ongoing follow-up into older ages for this long-running cohort will enable the association between mid to late-life factors and healthy ageing to be determined. This is particularly valuable for the examination of chronic diseases which have a 20–30 year prodrome and to provide knowledge on multiple morbidities. The dataset has a unique opportunity to improve our understanding of temporal relationships and the interactions between risk factors and comorbidities.

Electronic supplementary material

The online version of this article (doi:10.1186/s40695-016-0018-y) contains supplementary material, which is available to authorized users.

Impact of the National Health Service Health Check on cardiovascular disease risk: a difference-in-differences matching analysis

BACKGROUND

The National Health Service Health Check program in England is the largest cardiovascular risk assessment and management program in the world. We assessed the effect of this program on modelled risk of cardiovascular disease, individual risk factors for cardiovascular disease, prescribing of relevant medications and diagnosis of vascular disease.

METHODS

We obtained retrospective electronic medical records for a randomly selected sample of 138 788 patients aged 40-74 years registered with 462 English general practices participating in the Clinical Practice Research Datalink between 2009 and 2013. We used a quasi-experimental design of difference-indifferences matching analysis to compare changes in outcomes between Health Check attendees and nonattendees, with a median follow-up time of 2 years.

RESULTS

Overall, 21.4% of the eligible population attended a Health Check. After matching (n = 29 672 in each group), attendees had a significant absolute reduction in modelled risk for cardiovascular disease (-0.21%, 95% confidence interval [CI] -0.24% to -0.19%) and individual risk factors: systolic blood pressure (-2.51 mm Hg, 95% CI -2.77 to -2.25 mm Hg), diastolic blood pressure (-1.46 mm Hg, 95% CI -1.62 to -1.29 mm Hg), body mass index (-0.27, 95% CI -0.34 to -0.20) and total cholesterol (-0.15 mmol/L, 95% CI -0.18 to -0.13 mmol/L). Statins were prescribed for 39.9% of attendees who were at high risk for cardiovascular disease. The program resulted in significantly more diagnoses of selected vascular diseases among attendees, with the largest increases for hypertension (2.99%) and type 2 diabetes mellitus (1.31%).

INTERPRETATION

The National Health Service Health Check program had statistically significant but clinically modest impacts on modelled risk for cardiovascular disease and individual risk factors, although diagnosis of vascular disease increased. Overall program performance was substantially below national and international targets, which highlights the need for careful planning, monitoring and evaluation of similar initiatives internationally.

Predictive Risk Modelling to Prevent Child Maltreatment and Other Adverse Outcomes for Service Users: Inside the 'Black Box' of Machine Learning

Recent developments in digital technology have facilitated the recording and retrieval of administrative data from multiple sources about children and their families. Combined with new ways to mine such data using algorithms which can 'learn', it has been claimed that it is possible to develop tools that can predict which individual children within a population are most likely to be maltreated. The proposed benefit is that interventions can then be targeted to the most vulnerable children and their families to prevent maltreatment from occurring. As expertise in predictive modelling increases, the approach may also be applied in other areas of social work to predict and prevent adverse outcomes for vulnerable service users. In this article, a glimpse inside the 'black box' of predictive tools is provided to demonstrate how their development for use in social work may not be straightforward, given the nature of the data recorded about service users and service activity. The development of predictive risk modelling (PRM) in New Zealand is focused on as an example as it may be the first such tool to be applied as part of ongoing reforms to child protection services.

Improvement in Cardiovascular Risk Prediction with Electronic Health Records

The aim of this study was to compare the QRISKII, an electronic health data-based risk score, to the Framingham Risk Score (FRS) and atherosclerotic cardiovascular disease (ASCVD) score. Risk estimates were calculated for a cohort of 8783 patients, and the patients were followed up from November 29, 2012, through June 1, 2015, for a cardiovascular disease (CVD) event. During follow-up, 246 men and 247 women had a CVD event. Cohen's kappa statistic for the comparison of the QRISKII and FRS was 0.22 for men and 0.23 for women, with the QRISKII classifying more patients in the higher-risk groups. The QRISKII and ASCVD were more similar with kappa statistics of 0.49 for men and 0.51 for women. The QRISKII shows increased discrimination with area under the curve (AUC) statistics of 0.65 and 0.71, respectively, compared to the FRS (0.59 and 0.66) and ASCVD (0.63 and 0.69). These results demonstrate that incorporating additional data from the electronic health record (EHR) may improve CVD risk stratification.

Neighbourhood socioeconomic status and coronary heart disease in individuals between 40 and 50 years

OBJECTIVE

The incidence of myocardial infarction (MI) has decreased in general but not among younger middle-aged adults. We performed a cohort study of the association between neighbourhood socioeconomic status (SES) at the age of 40 and risk of MI before the age of 50 years.

METHODS

All individuals in Sweden were included in the year of their 40th birthday, if it occurred between 1998 and 2010. National registers were used to categorise neighbourhood SES into high, middle and low, and to retrieve information on incident MI and coronary heart disease (CHD). Cox regression models, adjusted for marital status, education level, immigrant status and region of residence, provided an estimate of the HRs and 95% CIs for MI or CHD.

RESULTS

Out of 587 933 men and 563 719 women, incident MI occurred in 2877 (0.48%) men and 932 (0.17%) women; and CHD occurred in 4400 (0.74%) men and 1756 (0.31%) women during a mean follow-up of 5.5 years. Using individuals living in middle-SES neighbourhoods as referents, living in high-SES neighbourhoods was associated with lower risk of MI in both sexes (HR (95% CI): men: 0.72 (0.64 to 0.82), women: 0.66 (0.53 to 0.81)); living in low-SES neighbourhoods was associated with a higher risk of MI (HR (95% CI): men: 1.31 (1.20 to 1.44), women: 1.28 (1.08 to 1.50)). Similar risk estimates for CHD were found.

CONCLUSIONS

The results of our study suggest an increased risk of MI and CHD among residents from low-SES neighbourhoods and a lower risk in those from high-SES neighbourhoods compared with residents in middle-SES neighbourhoods.